Editorial: Data Papers - Peer Reviewed Publication of High Quality Data Sets

This issue marks the launch of an undertaking by The International Journal of Robotics Research (IJRR) to solicit and publish a new genre of journal paper: a “data paper”. Our prime goal is to facilitate and encourage the release of high-quality, peer-reviewed datasets to the robotics community. We hope to implicitly create benchmark tests for use across many fields of robotics research. We recognize that acquiring high-calibre data is a substantial technical endeavour and one that need not be undertaken by every researcher. Indeed, the time and financial cost of experimental data capture can at worst be a barrier to entry and commonly slows algorithmic development. We wish to make it easier for authors to present original contributions and evaluate performance by processing established datasets. This, we hope, will have a twofold benefit to authors: first, there is no overhead in collecting experimental data; and second, it facilitates a direct comparison with work published previously. Beyond altruism, we are keen to provide a sufficient motivation for authors to release excellent, often hard-earned, experimental data. IJRR data papers will be treated in the same fashion as regular papers, undergoing the standard peer-review process and appearing in print in regular journal issues, and authors should expect their data papers to be cited just as regular papers are. The content of a data paper will of course be markedly different from a regular paper, not least because they are expected to be short affairs. Rather than standing alone, they should be considered as a companion to a website that will host the data and associated access tools. A data paper should provide a crisp statement of how the data was collected and a summary of its salient properties and intended audience. We leave a detailed description of a data paper to the author guidelines document on the IJRR website (see http://www.ijrr.org) but we stress that authors are encouraged to focus not on processing